cavis/libnd4j/include/ops/declarable/helpers/cuda/sequence_mask.cu

64 lines
2.7 KiB
Plaintext

/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://www.apache.org/licenses/LICENSE-2.0.
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
* License for the specific language governing permissions and limitations
* under the License.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
//
// @author GS <sgazeos@gmail.com>
//
#include <ops/declarable/helpers/sequence_mask.h>
namespace nd4j {
namespace ops {
namespace helpers {
template <typename I, typename B>
static __global__ void sequenceMaskKernel(void* inputBuf, Nd4jLong* inputShape, void* outputBuf, Nd4jLong* outputShape, int maxIndex) {
__shared__ I* input;
__shared__ B* output;
__shared__ Nd4jLong inputLen, outputLen;
if (threadIdx.x == 0) {
input = reinterpret_cast<I*>(inputBuf);
output = reinterpret_cast<B*>(outputBuf);
inputLen = shape::length(inputShape);
outputLen = shape::length(outputShape);
}
__syncthreads();
for (auto i = blockIdx.x; i < maxIndex; i += gridDim.x)
for(auto k = threadIdx.x; k < inputLen; k += blockDim.x)
if (i < input[shape::getIndexOffset(k, inputShape)])
output[shape::getIndexOffset(k * maxIndex + i, outputShape)] = B(true);
}
template <typename I, typename B>
static void sequenceMask_(LaunchContext* context, NDArray* input, NDArray* output, int maxIndex) {
dim3 launchDims(maxIndex, input->lengthOf(), 128);
NDArray::prepareSpecialUse({output}, {input});
auto stream = context->getCudaStream();
sequenceMaskKernel<I, B><<<launchDims.x, launchDims.y, launchDims.z, *stream>>>(input->specialBuffer(), input->specialShapeInfo(), output->specialBuffer(), output->specialShapeInfo(), maxIndex);
NDArray::registerSpecialUse({output}, {input});
}
void sequenceMask(nd4j::LaunchContext * context, NDArray* input, NDArray* output, int maxIndex) {
BUILD_DOUBLE_SELECTOR(input->dataType(), output->dataType(), sequenceMask_, (context, input, output, maxIndex), INTEGER_TYPES, LIBND4J_TYPES_EXTENDED);
}
BUILD_DOUBLE_TEMPLATE(template void sequenceMask_, (nd4j::LaunchContext* context, NDArray* input, NDArray* output, int maxIndex), INTEGER_TYPES, LIBND4J_TYPES_EXTENDED);
}
}
}